Author: Quan, Daniel; Luna Wong, LucÃa; Shallal, Anita; Madan, Raghav; Hamdan, Abel; Ahdi, Heaveen; Daneshvar, Amir; Mahajan, Manasi; Nasereldin, Mohamed; Van Harn, Meredith; Opara, Ijeoma Nnodim; Zervos, Marcus
Title: Impact of Race and Socioeconomic Status on Outcomes in Patients Hospitalized with COVID-19 Cord-id: 6jnrvkjq Document date: 2021_1_27
ID: 6jnrvkjq
Snippet: BACKGROUND: The impact of race and socioeconomic status on clinical outcomes has not been quantified in patients hospitalized with coronavirus disease 2019 (COVID-19). OBJECTIVE: To evaluate the association between patient sociodemographics and neighborhood disadvantage with frequencies of death, invasive mechanical ventilation (IMV), and intensive care unit (ICU) admission in patients hospitalized with COVID-19. DESIGN: Retrospective cohort study. SETTING: Four hospitals in an integrated health
Document: BACKGROUND: The impact of race and socioeconomic status on clinical outcomes has not been quantified in patients hospitalized with coronavirus disease 2019 (COVID-19). OBJECTIVE: To evaluate the association between patient sociodemographics and neighborhood disadvantage with frequencies of death, invasive mechanical ventilation (IMV), and intensive care unit (ICU) admission in patients hospitalized with COVID-19. DESIGN: Retrospective cohort study. SETTING: Four hospitals in an integrated health system serving southeast Michigan. PARTICIPANTS: Adult patients admitted to the hospital with a COVID-19 diagnosis confirmed by polymerase chain reaction. MAIN MEASURES: Patient sociodemographics, comorbidities, and clinical outcomes were collected. Neighborhood socioeconomic variables were obtained at the census tract level from the 2018 American Community Survey. Relationships between neighborhood median income and clinical outcomes were evaluated using multivariate logistic regression models, controlling for patient age, sex, race, Charlson Comorbidity Index, obesity, smoking status, and living environment. KEY RESULTS: Black patients lived in significantly poorer neighborhoods than White patients (median income: $34,758 (24,531–56,095) vs. $63,317 (49,850–85,776), p < 0.001) and were more likely to have Medicaid insurance (19.4% vs. 11.2%, p < 0.001). Patients from neighborhoods with lower median income were significantly more likely to require IMV (lowest quartile: 25.4%, highest quartile: 16.0%, p < 0.001) and ICU admission (35.2%, 19.9%, p < 0.001). After adjusting for age, sex, race, and comorbidities, higher neighborhood income ($10,000 increase) remained a significant negative predictor for IMV (OR: 0.95 (95% CI 0.91, 0.99), p = 0.02) and ICU admission (OR: 0.92 (95% CI 0.89, 0.96), p < 0.001). CONCLUSIONS: Neighborhood disadvantage, which is closely associated with race, is a predictor of poor clinical outcomes in COVID-19. Measures of neighborhood disadvantage should be used to inform policies that aim to reduce COVID-19 disparities in the Black community. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11606-020-06527-1.
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